d2 receptor genotype and striatal dopamine signaling predict motor cortical activity and behavior in...
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NeuroImage 54 (2011) 2915–2921
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D2 receptor genotype and striatal dopamine signaling predict motor cortical activityand behavior in humans
Leonardo Fazio a,b, Giuseppe Blasi a, Paolo Taurisano a, Apostolos Papazacharias a, Raffaella Romano a,Barbara Gelao a, Gianluca Ursini a, Tiziana Quarto a, Luciana Lo Bianco a, Annabella Di Giorgio a,b,Marina Mancini a, Teresa Popolizio b, Giuseppe Rubini c, Alessandro Bertolino a,b,⁎a Department of Neurological and Psychiatric Sciences, University of Bari “Aldo Moro”, Bari, Italyb Department of Neuroradiology, IRCCS “Casa Sollievo della Sofferenza”, San Giovanni Rotondo, FG, Italyc Department of Internal Medicine and of Public Medicine, University of Bari “Aldo Moro”, Bari, Italy
⁎ Corresponding author. Dipartimento di ScienzeUniversità degli Studi di Bari, Piazza Giulio Cesare, 11080 5593204.
E-mail address: [email protected] (A. Ber
1053-8119/$ – see front matter © 2010 Elsevier Inc. Aldoi:10.1016/j.neuroimage.2010.11.034
a b s t r a c t
a r t i c l e i n f oArticle history:
Received 30 June 2010Revised 8 November 2010Accepted 9 November 2010Available online 16 November 2010Keywords:Dopamine D2 Receptor PolymorphismMotor brain activityImaging geneticsMultimodalfMRI[123I] FP-CIT SPECT
Objective: Pre-synaptic D2 receptors regulate striatal dopamine release and DAT activity, key factors formodulation of motor pathways. A functional SNP of DRD2 (rs1076560 GNT) is associated with alternativesplicing such that the relative expression of D2S (mainly pre-synaptic) vs. D2L (mainly post-synaptic)receptor isoforms is decreased in subjects with the T allele with a putative increase of striatal dopamine levels.To evaluate how DRD2 genotype and striatal dopamine signaling predict motor cortical activity and behaviorin humans, we have investigated the association of rs1076560with BOLD fMRI activity during a motor task. Tofurther evaluate the relationship of this circuitry with dopamine signaling, we also explored the correlationbetween genotype based differences in motor brain activity and pre-synaptic striatal DAT binding measuredwith [123I] FP-CIT SPECT.Methods: Fifty healthy subjects, genotyped for DRD2 rs1076560 were studied with BOLD-fMRI at 3 T whileperforming a visually paced motor task with their right hand; eleven of these subjects also underwent [123I]FP-CIT SPECT. SPM5 random-effects models were used for statistical analyses.
Results: Subjects carrying the T allele had greater BOLD responses in left basal ganglia, thalamus,supplementary motor area, and primary motor cortex, whose activity was also negatively correlated withreaction time at the task. Moreover, left striatal DAT binding and activity of left supplementary motor areawere negatively correlated.Interpretation: The present results suggest that DRD2 genetic variation was associated with focusing ofresponses in the whole motor network, in which activity of predictable nodes was correlated with reactiontime and with striatal pre-synaptic dopamine signaling. Our results in humans may help shed light on geneticrisk for neurobiological mechanisms involved in the pathophysiology of disorders with dysregulation ofstriatal dopamine like Parkinson's disease.© 2010 Elsevier Inc. All rights reserved.
Introduction
The motor cortico-striatal thalamo-cortical (CSTC) circuit originatesfrom motor cortical areas (primary motor area—M1-, supplementarymotor area—SMA- and premotor area—PMA-), which send excitatoryglutamatergic projections to the striatum. Here, GABAergic mediumspiny neurons (MSNs) send inhibitory efferents to the internal segmentof the globus pallidus (GPi). From the GPi, other GABAergic projectionsreach directly or indirectly via the external part of the Globus Pallidus(GPe) the motor nuclei in the thalamus, which in turn send excitatory
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projections to motor cortical areas, completing the motor circuit (Joeland Weiner, 2000). Dopamine is a major modulator within striatumwhere its net effect is of increasing activity of thalamo-cortical pathwayswith facilitation of cortically initiated action (Mattay et al., 2002;Surmeier et al., 2007). D1 and D2 dopamine receptors exert differentactions on the direct and indirect pathways: striatal D1 receptors haveexcitatory effects on MSNs in the direct pathway, while D2 receptorsinhibit striatopallidal neurons of the indirect pathway (Nakano et al.,2000; Surmeier et al., 2007). Specific effects of D2 signaling in motorbehavior have been indicated by previous studies in animalmodels. Forexample, knock-out of D2 receptors and systemic administration of D2antagonists in mice impair locomotion and motor coordination(Aoyama et al., 2000; Kelly et al., 1998; Ralph et al., 2001); similarmotor alterations are also found after administration of D2 antagonistsdirectly in motor cortex (Molina-Luna et al., 2009), possibly by
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enhancement of intracortical excitability and signal transduction (Hospet al., 2009). However, these earlier studies did not distinguish betweenpre- and post-synaptic D2 receptors which are known to differentiallymodulate activity of striatal neurons (Khan et al., 1998; Lindgren et al.,2003; Tisch et al., 2004). Pre-synaptic D2 receptors aremore involved inmodulation of glutamate release, while post-synaptic receptors aremore involved in inhibition of GABA (Centonze et al., 2004).
Because of alternative splicing, D2 receptors exist in two isoforms, a“long” variant (D2L)which ismainly postsynaptic, and the “short” splicevariant (D2S) which has predominant pre-synaptic autoreceptorfunctions (Khan et al., 1998; Usiello et al., 2000). Recent studies suggestan association between relative expression of these two isoforms withan intronic single nucleotide polymorphism of the D2 receptor gene(DRD2 rs1076560 GNT): theminor (T) allele is associatedwith: reducedrelative expression of D2S in striatum and prefrontal cortex (Zhanget al., 2007); inefficient neural cortical and subcortical responses duringcognitive processing (Bertolino et al., 2009, 2010; Zhang et al., 2007);greater emotion control along with more resilient brain activity (Blasiet al., 2009) and reduced in vivo striatal binding of [123I] FP-CIT(Bertolino et al., 2010), a SPECT radioligandwhich binds to pre-synapticdopamine transporters (DAT) competing also with local dopaminelevels. This last association is consistent with the known role ofpre-synaptic D2 receptors in physically and functionally stimulatingDATs (Jones et al., 1999; Lee et al., 2007; Meiergerd et al., 1993; Scheffelet al., 1997).
The logical association between genetically determined dopamine D2receptor signaling andmotor related brain activity has not been explored.The purpose of the present study with multimodal imaging in healthysubjects was to investigate the association between the DRD2 rs1076560polymorphism and BOLD fMRI activity of the cortico-subcortical motorcircuit during a visually pacedmotor task. Consistentwith the known roleof dopamine in striatum(Tisch et al., 2004) andwith the association of theT allele with putative greater levels of striatal dopamine (Bertolino et al.,2010), we hypothesized that subjects carrying the T allele would havegreater responses in critical motor nodes. Given the above cited evidenceof the relationship between D2 receptors and activity of themotor cortex(Hosp et al., 2009; Molina-Luna et al., 2009) and to provide a behavioralcorrelate of genotype-based differences in brain activity, we alsohypothesized a correlation between activity in the cortical motor areasdistinguished by genotype and behavioral performance. Moreover, giventhe known functional and physical interaction between pre-synaptic D2receptors and DATs (Jones et al., 1999; Lee et al., 2007; Meiergerd et al.,1993; Scheffel et al., 1997), we explored in vivo the relationship betweenpre-synaptic striatal dopamine signaling and activity of the motorcircuitry, using [123I] FP-CIT SPECT measures of DAT binding and BOLDfMRI (Bertolino et al., 2006, 2009).
Methods
Subjects
Fifty healthy subjects (20 males, mean age 24.36±4.24)underwent fMRI and were selected from a larger sample of healthysubjects participating to our studies so that the two genotype groupswould be matched for demographics and for sample size. Exclusioncriteria included significant drug or alcohol abuse in the past sixmonths, head trauma with loss of consciousness, and any significantmedical condition. Handedness (Edinburgh Inventory: 0.76±0.24),socio-economic status (Hollingshead Four Factor Index: 31.87±13.31) and total IQ (WAIS-R: 110.37±15.34) were also measured.All these subjects underwent fMRI; a sub-sample of 11 individuals(6 males, mean age 24.36±3.13) was also studied with [123I] FP-CITSPECT. The present study was approved by the local IRB at theUniversity of Bari and written informed consent was obtained from allsubjects after the procedures had been fully explained to them.
Genotype determination
DRD2 rs1076560 genotypes were determined as previouslyreported (Zhang et al., 2007) and the two genotype groups included27 GG and 23 GT subjects in the fMRI sample and 4 GG and 7 GTsubjects in the SPECT sub-sample. Allelic distribution of this geneticvariant in the whole sample was in Hardy–Weinberg equilibrium(χ2=0.26; p=0.61). Furthermore, the distribution of DAT 3′ UTRVNTR genotype did not differ across the two DRD2 genotypes(χ2=0.05; p=0.83) ruling out potential stratification effectsfor this genetic variant with effects on dopamine signaling andcortico-subcortical activity (Bertolino et al., 2006, 2009).
Motor task
During performance of an attentional task (Blasi et al., 2007, 2005,2010; Zhang et al., 2007) all individuals performed a visually pacedmotor condition with their right hand. Subjects were instructed by acue arrow, pointing left or right, to press the corresponding button ona response box, as quickly and accurately as possible. All subjects weretrained on the task before the fMRI session. During the task, lasting10 m and 8 s, 66 arrow stimuli were presented, each for 800 ms. Afixation cross was presented during the interstimulus interval, with amean duration of 1670 ms (range 1180–5110 ms). During the task,further 175 attentional stimuli were also shown, each for 800 ms.Stimuli were presented via a back-projection system and behavioralresponses were recorded through a fiber-optic response box whichallowed measurement of accuracy and reaction time for each trial.
Data acquisition
fMRI data acquisitionBlood oxygen level-dependent (BOLD) fMRI was performed on a
GE Signa 3 T scanner (General Electric, Milwaukee, WI), equippedwith a standard quadrature head coil. A gradient-echo planar imagingsequence, (repetition time, 2000 ms; echo time, 28 ms; 26 interleavedaxial slices; thickness, 4 mm; gap, 1 mm; voxel size, 3.75 isotropic;scan repetition, 300; flip angle, 90°; field of view, 24 cm; matrix,64×64) was used to acquire images while subjects performed themotor task. The first four scans were discarded to allow for T1equilibration effect.
SPECT data acquisitionEach subject was injected intravenously with an average of
150 MBq (range 111–186 MBq) of commercially available [123I] FPCIT (GE Healthcare, Amersham, UK) (Booij et al., 1999) that binds todopamine transporters (Scheffel et al., 1997). Potassium Iodidesolution (Lugol) was administered at least 3 h before and 12 h afterradiopharmaceutical injection to block thyroid uptake of freeradioactive iodide. Images were acquired 3–6 h after [123I] FP-CITinjection (Seibyl et al., 2005) with a dual-head gamma camera(Infinia, General Electric) equipped with parallel-hole, low-energyhigh-resolution collimators. SPECT data were acquired using thefollowing parameters: 128×128 matrix, rotation of 360°, 60 views, 6°view angle, 45 s for projection. Slice thickness was 3.68 mm,acquisition time was 22 min; total brain countsN1 million wereachieved in all examinations. Reconstruction was performed by filteredback-projectionwithaButterworthfilter (cut-off frequency: 0.3 cycle/cm,10th order) to provide transaxial slices that were attenuation corrected.Attenuation correction was performed according to Chang's method(attenuation coefficient: 0.12 cm−1), after manually drawing anellipse around the head contour (Tatsch, 2002). System spatial resolution(full width at half-maximum) at a radius of rotation of 15.9 cm is 11 mm,as reported elsewhere (Soret et al., 2006). For analysis of striatalradiotracer uptake, slices were reoriented parallel to the canthomeatalline.
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Data analysis
Demographic and behavioral data analysisOne way, between groups ANOVAs and χ2 were used to evaluate
demographics as well as behavioral performance (accuracy andresponse time) across genotype groups.
fMRI data analysisAnalysis of the fMRI data was completed using Statistical
Parametric Mapping (SPM5; http://www.fil.ion.ucl.ac.uk/spm).Images, for each subject, were realigned to the first volume in thetime series to correct for head motion (b2.5 mm of translation, b2°rotation), spatially normalized into a standard stereotactic space(Montreal Institute on Neurology, MNI, template) and smoothedusing a 10 mm full-width half-maximum isotropic Gaussian kernel tominimize noise and to account for residual intersubject differences. Abox-car function, convolved with the hemodynamic response func-tion (HRF) at each voxel was modeled for each motor stimulus, usingthe timing of stimulus presentation. Timing of presentation of theattentional stimuli was also convolved with HRF, but not consideredfor further analysis. Subject-specific movement parameters, obtainedfrom the realignment procedure were included in the general linearmodel (GLM) as covariates, taking into account the effect of subjectmotion. In the first-level analysis, linear contrasts were computedproducing a t statistical maps at each voxel for the motor condition,assuming the fixation cross condition as a baseline.
All the individual motor contrast images were entered in a secondlevel random effects analysis. A one sample t-test (pb0.05, FalseDiscovery Rate—FDR—whole brain corrected; k=5), performed onthe whole group, was used to assess the functional network involvedin performance of the motor task, regardless of genotype. Results ofthis analysis were used to create a functional mask of motor activity toconstrain the genotype groups' analyses (see below). ANOVA betweenthe two genotype groups, with a statistical threshold of pb0.005,uncorrected, k=5, was used to evaluate main effects of DRD2rs1076560. Further False Discovery Rate (FDR) correction for multiplecomparisons at pb0.05 was used to identify significant responses inmotor brain regions. This was achieved by using a mask of functionalactivation in brain regions included in the CSTC motor circuit; the maskincluded 607 voxels reproducing the activity in M1, SMA, PMA, primarysensory area, caudate, putamen, pallidum and thalamus with a finalpb0.05, FDR-corrected. Brain regions were identified employing theWFUPickAtlas SPMToolbox (Maldjian et al., 2003). In addition, statisticalnonparametric correlations (Spearman's correlation) between individualreaction times and fMRI-BOLD signal changeof themotor cortical regionsdifferentially activated by the two genotype groups (see above) werecalculated outside SPM, using STATISTICA (StatSoft, Tulsa, Oklahoma)andwere subjected to a significance threshold of pb0.05. Individual fMRIBOLD mean signal change was extracted from the clusters differentiallyengaged by GG and GT subjects using the MarsBaR ROI toolbox for SPM(http://marsbar.sourceforge.net/).
Table 1Demographics, genetic, and behavioral data.
Demographic data
N Age Handedness Socio-econo
All 50 mean 24.4 0.76 31.8720 ♂ sd 4.24 0.24 13.31
GG 27 mean 24.8 0.75 34.9815 ♂ sd 4.73 0.24 12.35
GT 23 mean 23.9 0.77 28.0215 ♂ sd 3.62 0.24 13.73
SPECT data analysisSPECT data preprocessing was performed as previously reported
(Bertolino et al., 2010). Briefly, after spatial normalization on theSPECT template in MNI (Montreal Neurological Institute)space (Scherfler et al., 2005), a parametric image of specific tonon-displaceable equilibrium partition coefficient (V3″, a measureproportional to DAT binding potential) was obtained (Laruelle et al.,1994; Scherfler et al., 2005). Given the left lateralization of the motortask and of the fMRI findings (see below), [123I] FP-CIT V3″ data wereextracted in each subject using the WFU PickAtlas Toolbox for SPM(Maldjian et al., 2003) from a left and a right basal ganglia ROI whichincluded caudate and putamen. Spearman's correlations werecalculated with STATISTICA (StatSoft, Tulsa, Oklahoma) between[123I] FP-CIT uptake of the two basal ganglia ROIs and the meanfMRI-BOLD signal change of the clusters differentially engaged by thetwo genotype groups, as revealed by the ANOVA of the fMRI data.Correlation coefficients were subjected to a significance threshold ofpb0.05 Bonferroni-corrected for the number of the fMRI clusters inorder to minimize the chance of false-positive findings.
Results
Demographics, genetic, and behavioral data
Genotype groups were comparable for gender, age, handedness,socio-economic status, and IQ (all pN0.05). The two groups were alsowell matched in terms of accuracy (F48=1.59, p=0.21) and reactiontime (F48=0.37, p=0.54) at the fMRI task thus allowing analysis ofbrain activity in the absence of differences in behavioral performance(Table 1).
Functional imaging data
One-sample t-test of the whole sample indicated that performance ofthemotor task carriedoutwith the right hand activated themotor corticaland subcortical network, including primary motor and primarysomatosensory cortex, premotor and supplementarymotor area, caudate,putamen, globus pallidus and thalamus, especially in the left hemisphere.Parietal and occipital cortices were also consistently activated by thesubjects. Between-groups ANOVA indicated a highly significant effect ofDRD2 rs1076560 genotype: themain effect of genotypewas evident in leftputamen, globus pallidus, and thalamus (x,y,z=−22,−18,−5; k=172;Z=3.28; p=0.04, FDR-corrected), left primary motor area (precentralgyrus—BA4: x,y,z=−11,1,55; k=17; Z=3.23; p=0.04), left supple-mentary motor area (medial frontal gyrus—BA6: x,y,z=−59,−9,24;k=6; Z=3.22; p=0.04) and right putamen (x,y,z=22,18,−1; k=8;Z=2.62; p=0.04). In all these regions, statistical t-contrasts revealedgreater BOLD response inGT subjects. The opposite contrast (GGNGT) didnot reveal any cluster crossing the statistical threshold (Table 2, Fig. 1).
Spearman analysis demonstrated a negative correlation betweenBOLD response in M1 and reaction time at the task in GT subjects(Rho=−0.44, p=0.04) while no significant relationship in GG
Behavioral data
mics status IQ % Correct response Mean response time (ms)
110 99.79 572.7115 0.61 93.52
113 99.89 565.215 0.58 59.63
107 99.69 581.5315 0.64 122.99
Table 2Main effect of DRD2 rs1076560 during motor processing: regions significantly activated.
Coordinates Region (Brodmann's area) K p-FDR Z
−22 −18 5 L Putamen 172 0.04 3.28−19 −7 −4 L Lateral Globus Pallidus a 0.04 3.1−11 −29 1 L Thalamus a 0.04 2.98−11 7 55 L Medial Frontal Gyrus—SMA (BA 6) 17 0.04 3.23−59 −9 24 L Precentral Gyrus—M1 (BA 4) 6 0.04 3.2222 18 −1 R Putamen 8 0.04 2.62
Talairach's coordinates (x,z,y), anatomical regions with relative Brodmann's areas (BA),cluster size (K), FDR-corrected p level, and Z score. Abbreviations: L, left; R, right; SMA,supplementary motor area; M1, primary motor cortex.
a Same cluster.
Fig. 2. Correlation between fMRI response in M1 and individual reaction times.Scatterplots of Spearman's analyses showing a negative correlation between meanreaction times and BOLD signal change of left M1 in GT subjects (Rho=−0.44;p=0.004) (A), while no significant correlation in GG subjects (B).
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Rho=0.17, p=0.3). These correlations were significantly differentfrom each other (p=0.04). No significant correlation was foundbetween SMA BOLD response and performance in both genotypegroups (all Rhob0.15) (Fig. 2). In addition, an explorative fMRIanalysis correlating individual reaction times with functional brainactivity in all motor regions was performed in all subjects regardlessof genotype. A weak statistical effect was found indicating a negativerelationship between reaction time at the task and activity in left M1(BA4: x,y,z=−41,−12,52; k=11; Z=1.97; p uncorrected=0.025).However, this correlation failed to reach statistical significance aftercorrection for multiple comparisons.
Correlation between fMRI and [123I] FP-CIT SPECT data
Spearman's analysis demonstrated a significant negative correlationbetween left [123I] FP-CIT striatal binding and BOLD signal change of theleft SMA (Rho=−0.79; p=0.003, Bonferroni-corrected p=0.015). Nosignificant correlation was detected between left striatal [123I] FP-CITuptake and BOLD signal change measured in the other brain areasdifferentially engaged by the two genotype groups (left M1, left or right
Fig. 1. Main effect of DRD2 rs1076560 genotype during performance of the motor task.Results of the ANOVA in SPM5 shown in (A) three-dimensional rendering and in(B) sagittal, coronal and axial MRI sections. Images were thresholded at p=0.05 FDRcorrected; the color bar indicates z values of the difference in BOLD signal betweengenotype groups. (C) Graph showing differences between genotype groups on BOLDsignal change in supplementary motor area (SMA), primary motor cortex (M1),putamen (PUT), thalamus (THAL) and globus pallidus, pars externa (GPE).
basal ganglia). A statistical trend was evident for the correlationbetween right [123I] FP-CIT striatal binding and activity in left SMA(Rho=−0.67; Bonferroni-corrected p=0.09) while no significantcorrelation with activity in the other brain regions (Fig. 3). Due to therelatively small sample size, genotype effects could not be investigatedin this sub-sample. Nevertheless, it is important to note that in this sub-sample subjects carrying the T allele still had greater fMRI-BOLD
Fig. 3. Correlation between fMRI and [123I] FP-CIT SPECT.Scatterplot of Spearman'sanalysis showing a negative correlation between [123I] FP-CIT V3″ binding in left basalganglia and BOLD signal change of the left SMA (Rho=−0.79; p=0.003, Bonferroni-corrected p=0.015).
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responses in motor regions identified in the larger sample (SMA:GG=0.567, GT=1.108; M1: GG=0.839, GT=1.051; left BG:GG=0.261, GT=0.662; right BG: GG=0.073, GT=0.514).
Discussion
The present study demonstrates association of DRD2 rs1076560genotypewith activity of cortico-subcortical motor regions.We reportgreater fMRI BOLD responses in putamen, globus pallidus andthalamus, as well in SMA and M1 of GT subjects during a simplevisually paced motor task. The T allele of DRD2 rs1076560 has beenassociated with reduced expression of the D2S autoreceptors (Zhanget al., 2007) which physiologically contribute to inhibit dopaminerelease.
These results were evident despite absence of any significantbehavioral difference between genotype groups, suggesting that GTsubjects require greater recruitment of neuronal resources duringmotor processing. To the extent that greater demands of motorprocessing require greater activation of brain motor regions (Gutet al., 2007; Verstynen et al., 2005) and that task practice is correlatedwith decreased motor activation (Ma et al., 2010), motor efficiencycan be defined as lesser activation of brain regions in response to amotor task within the context of similar behavioral performance.From this perspective, these data are consistent with previouspublished fMRI studies indicating less efficient brain activity in GTsubjects during performance of working memory and attentionalcontrol tasks, in terms of greater activity of cortical and subcorticaltask-related brain regions (Bertolino et al., 2009, 2010; Zhang et al.,2007). A more mechanistic account of the present results is alsopossible as these results may reflect the role of pre-synaptic D2autoreceptors in inhibiting striatal dopamine release. Pre-synaptic D2receptors exert a negative feedback on dopaminergic firing into thesynaptic cleft (Watanabe et al., 2009). Lower density of pre-synapticD2 receptors in GT carriers should therefore result in stronger (lessinhibited) dopaminergic firing leading to stronger dopamine signalsat the postsynaptic site. Hence, greater activation of cortical andsubcortical motor regions in GT subjects could simply stem fromstronger dopamine signals in the striatum, where dopamine exerts itsfacilitating modulatory influence on actions prepared by the cortex(Tisch et al., 2004). This interpretation is also consistent with thenegative correlation between activity in SMA and striatal FP-CITbinding (vide infra). In the context of motor behavior, thisinterpretation is also consistentwith experimental and clinical studiesof striatal dopamine dysregulation eliciting reduction of selectivity ofsomatotopic neuronal responses to peripheral stimulation in corticalmotor areas and basal ganglia (Filion et al., 1988) as well as greatermotor cortical excitability (Cantello et al., 1996; Lefaucheur, 2005).
The main genotype differences appear mainly left lateralized, afinding consistent with the fact that the task was carried out with theright hand only. The regional localization of differences between thetwo genotype groups can be explained with the known neurobiologyof dopamine D2 signaling within the motor circuitry. The effect ofDRD2 rs1076560 genotype was evident in striatum, in which D2receptors are abundantly expressed (Jackson and Westlind-Daniels-son, 1994) both pre-synaptically on dopamine terminals from thesubstantia nigra pars compacta and post-synaptically on GABAmedium spiny neurons (Khan et al., 1998; Lindgren et al., 2003).Large effects were also evident in globus pallidus and in thalamus, thelatter being the main target of striatal medium spiny neurons in thedirect and in the indirect pathways. Finally, large effects were alsofound in M1 and in SMA, regions which provide inputs and receiveprojections from the motor CSTC circuit (Nakano et al., 2000).Although both these cortical regions contribute to provide stimulationto the CSTCmotor circuit, several studies agree in indicating the SMA asthe principal target of this circuit (Sakai et al., 1999; Schell and Strick,1984; Wiesendanger and Wiesendanger, 1985). Thus, differential
engagement of SMA in the two genotype groupsmay be directly relatedto dopamine-facilitated recruitment and activity of striatal and thalamicregions. On the other hand, greater activity of M1 in GT subjects can bespeculatively explained as a modulatory effect of the SMA on the M1descendent motoneurons (Serrien et al., 2002). These contentions areconsistent with the correlations we have demonstrated. Striatal DATbindingwas correlated with activity in SMA but not in M1. On the otherhand, reaction time at the taskwas correlatedwith activity inM1 (greateractivity for faster responses) but not in SMA. These correlations suggesta relatively specific relationship of these two cortical areas withpre-synaptic striatal dopamine signaling and with behavioral perfor-mance (see below).
While differences between the two genotype groups in terms ofcortical and subcortical engagementwere left lateralized (contralateral),a significant effect of genotype was also evident in right putamen(ipsilateral to the hand involved in the task). The presence of ipsilateralbrain activity during a motor task is supported by abundant evidence:electrophysiological studies in monkeys reported that approximately10% of the descending corticospinal projections remain uncrossed andare involved in contralateral limb movement (Tanji et al., 1988). Inhumans, electrophysiological (Chen et al., 1997) and functionalneuroimaging studies (Mattay et al., 1997; Verstynen et al., 2005)reported ipsilateral motor cortex activity during hand movementsrelated to task complexity. Moreover, other functional imaging experi-ments have reported strong functional connectivity between the left andthe right striatum during rest (Di Martino et al., 2009) as well as duringright hand motor tasks (Marchand et al., 2008; Postuma and Dagher,2006).
Our data also demonstrate a negative correlation between striatal[123I] FP-CIT binding and SMA BOLD fMRI response. Resting state [123I]FP-CIT measures are directly proportional to affinity or density ofDATs and are inversely related to dopamine levels (Scheffel et al.,1997). Striatal D2S autoreceptors regulate DA release and synthesis(Jackson and Westlind-Danielsson, 1994; Lindgren et al., 2003), andthey stimulate DAT activity and density (Parish et al., 2001).Therefore, with the present data we cannot ascertain whether thecorrelation is because of DAT density or of dopamine levels. However,greater dopamine levels of dopamine are known to be related withgreater subcortical excitatory feedback to the cortex (Tisch et al.,2004), especially to the SMA (Heinz et al., 1999; Sakai et al., 1999;Schell and Strick, 1984; Wiesendanger and Wiesendanger, 1985).Thus, we speculate that the correlation between SPECT and fMRI datais because of striatal levels of dopamine.
Our study involved healthy subjects only and no direct conclusioncan be drawn about pathophysiology of brain disorders involvingstriatal dopamine D2 signaling and motor activity. However, somespeculations about Parkinson's disease (PD) can bemade. In this regard,recent theories have proposed that dopamine D2 dysregulation of thebalance between direct and indirect striatal pathways is associatedwithmotor cortical alterations and with motor symptoms like bradykinesia(Rodriguez-Oroz et al., 2009). Indeed, a series of studies provideexperimental support for D2 receptor involvement in PD and for controlof signal-to-noise inmotor circuitry by striatal dopamine levels (Boraudet al., 2000; Drew et al., 2007; Filion et al., 1988; Goldberg et al., 2004;Tinsley et al., 2009). Consistently, primary motor cortex responses areincreased in patients with PD (Cantello et al., 1996; Lefaucheur, 2005);exaggerated responses in the motor circuitry including the SMA arerelated to dopamine levels (Mattay et al., 2002) and striato-frontalconnectivity (Jahanshahi et al., 2010). These studies together suggestthe possibility that dysregulation of striatal dopamine D2 receptorsignaling is associated with cortico-subcortical neural alterations andbehavioral symptoms found in PD. Indeed, herewe recapitulate some ofthese alterations demonstrating exaggerated responses of the motorcircuit, a relationship between activity in M1 and behavioral responsesat the task, and greater activity in SMA being predicted by putativereduced levels of pre-synaptic striatal dopamine signaling.
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Limitations
Although we studied a sample of 50 subjects, only 11 of themunderwent SPECT and thus only a relatively small part of the samplewasinvestigated with a multimodal approach. However, to the extent thatour purpose was to determine if striatal dopamine levels might becorrelated with greater BOLD response in brain regions differentiallyengagedbygenotype, the applied statistics canbe regardedas robust.Ourresults indicate that around 60% of the variance of the activity in SMA isexplained by the correlation with striatal FPCIT binding and survive astringent Bonferroni correction for multiple comparisons.
Earlier studies have demonstrated an inverse correlation betweenactivity of motor brain regions and behavioral performance duringmotor tasks (Mohamed et al., 2004; Oguz et al., 2003). Albeitstatistically weak, our results in the whole sample (independent ofgenotype) are consistent with these earlier studies suggesting anegative correlation. Several factors may have contributed to ourresults being weaker than earlier studies, including age and difficultyof the motor task. In the present study, we have evaluated a sample ofyoung healthy adults (mean age 24 years, range 20–39) performing asimple motor task. Indeed, both aging and greater demands of motorprocessing are known to increase variance and activity in motor brainregions (Gut et al., 2007; Verstynen et al., 2005).
Conclusions
In conclusion, the present data may shed light on dopamine D2related genetic risk for alteration of specific neural mechanismswithin the striato-thalamo-cortical circuit controllingmotor behavior.We believe these data in healthy subjects represent a recapitulation ofsome aspects of the pathophysiology of Parkinson's disease.
Acknowledgment
We would like to acknowledge Grazia Caforio, Riccarda Lomuscio,Rita Masellis, Annamaria Porcelli, Madia Lozupone, Marco Pisciotta,and Artor Niccoli-Asabella, for their help with data acquisition, and allthe people who participated in this study.
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